Dataset Information

Proteomic discovery of diabetic nephropathy biomarkers.

ABSTRACT: Diabetes mellitus (DM) is a complex systemic disease with complications that result from both genetic predisposition and dysregulated metabolic pathways. It is highly prevalent, with current estimates stating that there are 17.5 million diagnosed and 6.6 million undiagnosed patients with diabetes in the United States. DM and its complications impose a significant societal and economic burden. The medical costs of common microvascular complications of uncontrolled DM, diabetic nephropathy (DN) and diabetic retinopathy account for 29% and 15%, respectively, of the $116 billion worth expenditures associated with diabetes. A substantial gap exists in our knowledge related to the understanding of these complications. To advance therapy and decrease the societal burden of DM, there is a clear need for biomarkers that can diagnose DN at an early stage and predict its course. Proteomics has evolved into a high-throughput, analytical discipline used to analyze complex biological data sets. These open-ended, hypothesis-generating approaches, when appropriately designed and interpreted, are well suited to the study of the pathogenic mechanisms of diabetic microvascular disease and the identification of biomarkers of DN. In this study, we review the evolving role played by proteomics in expanding our understanding of the diagnosis and pathogenesis of DN.

SUBMITTER: Merchant ML

PROVIDER: S-EPMC2987606 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Proteomic discovery of diabetic nephropathy biomarkers.

Merchant Michael L ML Klein Jon B JB

Advances in chronic kidney disease 20101101 6

Diabetes mellitus (DM) is a complex systemic disease with complications that result from both genetic predisposition and dysregulated metabolic pathways. It is highly prevalent, with current estimates stating that there are 17.5 million diagnosed and 6.6 million undiagnosed patients with diabetes in the United States. DM and its complications impose a significant societal and economic burden. The medical costs of common microvascular complications of uncontrolled DM, diabetic nephropathy (DN) an ...[more]

PMID: 21044770

Similar Datasets

Project description:Validation of predicted gene expression of human mesangial cells after 24h Tacrolimus stimulus Objective: To evaluate tacrolimus as therapeutic option for diabetic nephropathy (DN) based on molecular profile and network-based molecular model comparisons. Materials and Methods: We generated molecular models representing pathophysiological mechanisms of DN and tacrolimus mechanism of action (MoA) based on literature derived data and transcriptomics datasets. Shared enriched molecular pathways were identified based on both model datasets. A newly generated transcriptomics dataset studying the effect of tacrolimus on mesangial cells in vitro was added to identify mechanisms in DN pathophysiology. We searched for features in interference between the DN molecular model and the tacrolimus MoA molecular model already holding annotation evidence as diagnostic or prognostic biomarker in the context of DN. Results: Thirty nine molecular features were shared between the DN molecular model, holding 252 molecular features and the tacrolimus MoA molecular model, holding 209 molecular features, with six additional molecular features affected by tacrolimus in mesangial cells. Significantly affected molecular pathways by both molecular model sets included cytokine-cytokine receptor interactions, adherens junctions, TGF-beta signaling, MAPK signaling, and calcium signaling. Molecular features involved in inflammation and immune response contributing to DN progression were significantly downregulated by tacrolimus (e.g. the tumor necrosis factor alpha (TNF), interleukin 4, or interleukin 10). On the other hand, pro-fibrotic stimuli being detrimental to renal function were induced by tacrolimus like the transforming growth factor beta 1 (TGFB1), endothelin 1 (EDN1), or type IV collagen alpha 1 (COL4A1). Conclusion: Patients with DN and elevated TNF levels might benefit from tacrolimus treatment regarding maintaining GFR and reducing inflammation. TGFB1 and EDN1 are proposed as monitoring markers to assess degree of renal damage. Next to this stratification approach, the use of drug combinations consisting of tacrolimus in addition to ACE inhibitors, angiotensin receptor blockers, TGFB1- or EDN1-receptor antagonists might warrant further studies. comparison of gene expression of human mesangial cells after 24h Tacrolimus vs. Ctrl; 4 independent experiments were conducted (4xTacrolimus 24h and 4x ctrl. 24h with Drug solvent (DMSO))

Dataset Information

Proteomic discovery of diabetic nephropathy biomarkers.

Publications

Proteomic discovery of diabetic nephropathy biomarkers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets